Triple
T2061716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mehmet Akif Ersoy |
E45804
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Ersoy
Ersoy is a Turkish surname most notably borne by Mehmet Akif Ersoy, the poet of the Turkish National Anthem.
|
E230809
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ersoy | Statement: [Mehmet Akif Ersoy, familyName, Ersoy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ersoy Context triple: [Mehmet Akif Ersoy, familyName, Ersoy]
-
A.
Seyhun
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
-
B.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
-
C.
Feridun Zaimoglu
Feridun Zaimoglu is a German-Turkish author and artist known for his influential novels, essays, and plays that explore migration, identity, and multicultural life in Germany.
-
D.
Kerim Bey
Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
-
E.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ersoy Triple: [Mehmet Akif Ersoy, familyName, Ersoy]
Generated description
Ersoy is a Turkish surname most notably borne by Mehmet Akif Ersoy, the poet of the Turkish National Anthem.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ersoy Target entity description: Ersoy is a Turkish surname most notably borne by Mehmet Akif Ersoy, the poet of the Turkish National Anthem.
-
A.
Seyhun
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
-
B.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
-
C.
Feridun Zaimoglu
Feridun Zaimoglu is a German-Turkish author and artist known for his influential novels, essays, and plays that explore migration, identity, and multicultural life in Germany.
-
D.
Kerim Bey
Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
-
E.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a8891b38288190abd572ccad9b6928 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9d0ecf08190aec20338a6ba9911 |
completed | March 7, 2026, 5:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae271fa66081908be6c685b9bd8aa4 |
completed | March 9, 2026, 1:49 a.m. |
| NEDg | Description generation | batch_69ae28b4f0548190926ac694fbade405 |
completed | March 9, 2026, 1:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae292a9d7481909acbc3a5f24ff0b9 |
completed | March 9, 2026, 1:58 a.m. |
Created at: March 4, 2026, 7:40 p.m.